Discovering Functional Dependencies for Multidimensional
Design

Nowadays, it is widely accepted that the data warehouse design
task should be largely automated. Furthermore, the data warehouse
conceptual schema must be structured according to the
multidimensional model and as a consequence, the most common way to
automatically look for subjects and dimensions of analysis is by
discovering functional dependencies (as dimensions functionally
depend on the fact) over the data sources. Most advanced methods
for automating the design of the data warehouse carry out this
process from relational OLTP systems, assuming that a RDBMS is the
most common kind of data source we may find, and taking as starting
point a relational schema. In contrast, in our approach we propose
to rely instead on a conceptual representation of the domain of
interest formalized through a domain ontology expressed in the
DL-Lite Description Logic. We propose an algorithm to discover
functional dependencies from the domain ontology that exploits the
inference capabilities of DL-Lite, thus fully taking into account
the semantics of the domain. We also provide an evaluation of our
approach in a real-world scenario.